Significance of pH control in anammox process performance at low temperature

Accepted Manuscript Significance of pH control in anammox process performance at low temperature Mariusz Tomaszewski, Grzegorz Cema, Aleksandra Ziembińska-Buczyńska PII:

S0045-6535(17)31077-9

DOI:

10.1016/j.chemosphere.2017.07.034

Reference:

CHEM 19567

To appear in:

ECSN

Received Date: 9 April 2017 Revised Date:

4 July 2017

Accepted Date: 8 July 2017

Please cite this article as: Tomaszewski, M., Cema, G., Ziembińska-Buczyńska, A., Significance of pH control in anammox process performance at low temperature, Chemosphere (2017), doi: 10.1016/ j.chemosphere.2017.07.034. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

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Mariusz Tomaszewski*, Grzegorz Cema, Aleksandra Ziembińska-Buczyńska

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The Silesian University of Technology, Environmental Biotechnology Department, Akademicka 2, 44-100 Gliwice, Poland (*[email protected])

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Key words: anammox; nitrogen; pH; statistical analysis; temperature

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Significance of pH control in anammox process performance at low temperature

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Abstract

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Anaerobic ammonium oxidation (anammox) is an efficient process for biological nitrogen

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removal from wastewater. Common use of this technology is still limited by relatively high

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optimal temperature. Temperature and pH influence on the anammox process was widely

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studied, but the significance of pH control in the anammox performance at low temperature

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was omitted. Moreover up to now, these two parameters were analyzed separately without

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looking into the composite effects. Statistical approach was used to conduct an in-depth study

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of the individual and interactive influence of pH and low temperature on the anammox

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activity. Optimal pH was observed between 7.0-7.5, but results indicate that there is no

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statistically significant interaction between pH and temperature. However, it was observed

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that the optimal pH range narrows along with the temperature decrease, which means that the

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efficiency of the anammox process at low temperatures can be improved by correction and

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adequate control of pH.

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1. Introduction

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Anaerobic ammonium oxidation (anammox) is an innovative process for biological nitrogen

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removal from nitrogen-rich wastewater with organic carbon deficiency. In the anammox

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process, ammonia nitrogen is anaerobically oxidised to molecular nitrogen by Planctomycete-

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type bacteria, with the nitrites used as an electron acceptor. Compared to conventional 1

ACCEPTED MANUSCRIPT biological processes (nitrification and denitrification), anammox does not require oxygen and

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organic carbon. As a result, partial nitritation - anammox allows to reduce oxygen demand (by

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ca. 60%) and to eliminate the need for an external organic carbon source [Lackner et al.,

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2014; Ma et al., 2016]. Combined with the smaller excess sludge production (by 92%) [Ma et

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al., 2016] anammox helps to significantly reduce costs by up to 90% [Jetten et al., 2001]. In

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addition, anammox has a higher removal rate, requires a smaller bioreactor volume due to a

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smaller amount of excess sludge production and emits smaller amounts of greenhouse gases

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(including CO2 and N2O) [Nozhevnikova et al., 2012; Ma et al., 2016]. While anammox is

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already being used in full-scale wastewater treatment plants, extensive use of this process

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continues to be difficult because of the high biomass sensitivity to conditions variation, such

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as that of the pH, temperature or substrate concentration [Jin et al., 2012]. Biomass

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regeneration after the physicochemical factors have caused damage is time-consuming

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because of the long anammox bacteria doubling time (7 – 11 days) [Kartal et al., 2012]. This

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implies that gaining more knowledge on the affecting factors is crucial for effective and stable

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process performance.

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Temperature and pH are crucial parameters for microbial growth and activity. The optimum

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temperature for most anammox bacteria that are used in wastewater treatment has been

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reported as being between 30 and 40˚C [Strous et al., 1999; Egli et al., 2001; Jin et al., 2012].

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For this reason, the anammox process is usually used for treatment of reject water after

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dewatering of digested sludge, as this kind of wastewater usually has a high temperature (25 –

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35°C). However, the optimum temperature for anammox is much higher than the average

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temperature of municipal wastewater. This constitutes one of the main problems for common

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use of this process in the main stream of the wastewater treatment plant instead of that of the

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combination of nitrification and denitrification. Therefore, implementation of effective

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anammox below its optimal temperature seems to be one of the most challenging but also

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ACCEPTED MANUSCRIPT profitable processes. The optimum pH for the growth and activity of anammox bacteria used

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in wastewater treatment was reported to be in the range of 7.2 to 7.6 [Puyol et al., 2014b;

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Carvajal-Arroyo et al., 2014; Lu et al., 2016], but activity was also observed for a wider

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range, i.e. from 6.5 to 9.3 [Egli et al., 2001; Tang et al., 2010; Jin et al., 2012]. In addition to

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the direct impact, both temperature and pH influence the concentrations of free ammonia (FA)

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and free nitrous acid (FNA), which have been reported as anammox inhibitors [Fernandez et

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al., 2012]. Based on the central composite design (CCD), Daverey et al. [2015] reported that

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interaction between temperature (in the range of 21.9 – 43.1˚C) and pH (in the range of 5.38 –

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9.62) is statistically significant. They also assumed that the negative effect of low temperature

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can be compensated by higher pH, but this interesting conclusion was reached based on only

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two experimental sets (beyond the CCD design) for one temperature (15˚C) with pH 6.5 and

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7.5. The influence of temperature and pH on anammox bacteria has been studied extensively

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in recent years, but the simultaneous effects of the two parameters, particularly at low

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temperatures, is still unclear and has not been studied so far.

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Statistical methods are powerful tools to find the optimal values of process parameters along

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with their interactive effects on the response. These methods are widely used for bioprocess

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optimisation and have also successfully been used in the field of environmental science

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[Daverey et al., 2015]. The central composite design followed by response surface

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methodology (RSM) can be used to obtain a mathematical relationship for independent and

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simultaneous temperature and pH influence on anammox activity, which can then be

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approximated by the polynomial quadratic equation [StatSoft, 2013]. As shown in the

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graphical representation of CCD (Supplementary Figure 1), it consists of 9 experimental set-

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ups for k = 2 factors analysis. The centre point and k2 factorial points are required for the

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first-order regression coefficients, while 2·k axial points allow to estimate the second-order

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ACCEPTED MANUSCRIPT model. The distance from the factorial and axial points to the centre point is the same and is α

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= √k, which gives a spherical, rotatable design.

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The main objective of this work was to conduct an in-depth investigation of the influence of

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temperature and pH on the anammox process. Both the individual influence of pH and

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temperature as well as their interactive effects on the activity of anammox bacteria were

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studied.

2. Materials and methods

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2.1.Anammox biomass

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The anammox suspended biomass used in all of the assays originated from a laboratory-scale

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sequencing batch reactor (SBR) and was dominated by anammox bacteria of the genus

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Candidatus Jettenia (which was evaluated based on a metagenomic analysis – data not

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shown). The reactor was operated at a temperature of 31.6±0.9°C, pH 7.8±0.3 and was fed

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with a mineral medium with a total nitrogen loading rate of 0.408±0.086 g N·L-1·d-1. Mineral

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medium composition adapted from [van de Graaf et al., 1996]: 0.725 g NH4Cl·L-1, 1.268 g

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NaNO2·L-1, 0.048 g KHCO3·L-1, 0.041 g KH2PO4·L-1, 0.228 g MgSO4· 7 H2O·L-1, 0.007 g

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FeSO4· 7 H2O·L-1, 0.004 g EDTA·L-1. For the batch tests, biomass samples with the medium

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were prepared in 1 L batch anaerobic reactors and left for 20 hours in a thermostatic cabinet

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(POL-EKO-APARATURA) to remove all ammonium and nitrite nitrogen and to reach the

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desired temperature.

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2.2.Batch tests

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A phosphate buffer was added to the batch reactors (to reach a final concentration of 0.14

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g KH2PO4·L-1 and 0.75 g K2HPO4·L-1) and the pH was adjusted to the target value by using

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10% HCl or 10% NaOH and a pH meter (WTW pH 330i). The samples were purged with

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dinitrogen gas to remove any dissolved oxygen. The tests were performed in duplicate; in a 1 4

ACCEPTED MANUSCRIPT L volume, with mixing at 150 rpm, an average biomass concentration of 1.0±0.2 g VSS·L-1

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and with equal initial concentrations of anammox substrates, i.e. ammonium and nitrite

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nitrogen (30 mgN·L-1), in the form of NH4Cl and NaNO2. Samples from the batch test

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reactors were periodically collected during the tests (1.5 – 3 hours, depending on the rate of

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reaction), filtered and stored for 0.5 – 3.5 hours at 4 °C for N-NH4, N-NO2 and N-NO3

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concentration measurement. Concentrations of ammonium, nitrite and nitrate nitrogen were

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determined by fast photometric tests (MERCK Millipore) with a photometer (MERCK

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Spectroquant® NOVA60). Specific anammox activity (SAA) was calculated based on a

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decrease in inorganic nitrogen in the linear range of substrates removal and expressed as

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gN·gVSS-1·d-1.

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2.3. Experimental set-up

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Experiments on the influence of temperature were conducted at: 10, 15, 20, 25, 30, 35 and 40

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°C with a constant pH value of 7.5, while experiments on the influence of pH were conducted

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at: 6.0, 6.5, 7.0, 7.5, 8.0, 8.5 and 9.0 with a constant temperature of 30°C.

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The full CCD experimental set-up is shown in Table 3 (Results and discussion). It consisted

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of 12 experimental sets, including four replications at centre point in order to improve

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precision of the experiment. The temperature range was chosen to study the relationship

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between pH and temperature below optimal range. The temperature and pH values were

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evaluated at five different coded levels represented as: -α ≈ -1.41, -1, 0, +1 and +α ≈ 1.41.

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Temperature natural values were: -α = 10°C, -1 = 13°C, 0 = 20°C, +1 = 27 °C and +α = 30°C,

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while pH natural values were: -α = 6.5, -1 = 6.8, 0 = 7.5, +1 = 8.2 and +α = 8.5.

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Statistical software (STATISTICA StatSoft®) was used for analysis of the CCD experiment.

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Based on regression analysis, coefficients of the second-order polynomial equation were

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calculated. The equation describes the relationship between the independent variables

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(temperature and pH) and the response, which is distinct anammox activity. Finally, the

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obtained mathematical model was tested using analysis of variance (ANOVA).

3. Results and discussion

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3.1.Individual temperature influence

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The test results show a nearly linear dependence of anammox bacteria activity in the

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temperature range of 10 to 40 °C (Figure 1A). The highest anammox activity was obtained at

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40 °C (0.857 gN·gVSS-1·d-1) and the lowest at 10 °C (0.032 gN·gVSS-1·d-1) at a constant pH

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of 7.5. The tested biomass was dominated by anammox bacteria of the genus Candidatus

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Jettenia. Ali et al. [2015] reported growth of C. Jettenia caeni in a temperature range of 20 °C

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to 42.5°C, with the optimum at 37°C.

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The results are similar and consistent with other reports [Dosta et al., 2008; Sobotka et al.,

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2015; Lotti et al., 2015]. Dosta et al. [2008] observed an exponential increase in activity

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between 10 and 40˚C, i.e. from ca. 0.02 to 0.18 gN·gVSS-1·d-1. Inhibition (probably caused by

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biomass lysis) was noticed at 45˚C. Similar results were obtained for both granular and

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biofilm anammox biomass cultivated at ca. 30˚C. Sobotka et al. [2015] also used a granular

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biomass cultivated at 30˚C. In their experiment, the temperature dependence profile in the

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same temperature range (10 - 40˚C) was nearly linear, i.e. from 0 to 1.3 g N g VSS-1d-1. In

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another recent report, Lotti et al. [2015] evaluated the temperature effects (from 10 to 30˚C)

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during adaptation to cold conditions, i.e. on a biomass cultivated at 30˚C, after 8 months of

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cultivation at 20˚C and after 6 months of cultivation at 10˚C. This interesting study proved

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that anammox bacteria can adapt to lower temperatures after long-term cultivation in 20˚C

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and 10˚C and that the adapted biomass had a higher SAA at low temperatures than the non-

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adapted biomass. Adaptation is a natural phenomenon among bacteria, and temperature

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ACCEPTED MANUSCRIPT adaptation of anammox bacteria has been studied and proved by many authors [Dosta et al.,

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2008; Isaka et al., 2008; Lotti et al., 2015].

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An Arrhenius equation (equation 1) was used to calculate the activation energy (Ea); the

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Arrhenius plots are shown in Figure 1B. The activation energy calculated in the range of 10-

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40˚C is equal to 72 kJ/mol and is similar to other reported values: 70 kJ/mol [Strous et al.,

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1999], 63 kJ/mol [Dosta et al., 2008], and 76 kJ/mol [Sobotka et al., 2015]. k = A exp(-Ea/RT) (1)

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where:

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k – rate constant,

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A – pre-exponential factor,

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Ea – activation energy,

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R – gas constant,

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T – temperature.

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Figure 1.

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However, the coefficient of determination (R2) for linear regression of the data set for the full

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tested range (10 - 40˚C) was equal to 0.89, thus indicating that a single regression line did not

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exactly describe the effect of temperature. A similar observation was made by Isaka et al.

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[2008] and Lotti et al. [2015]. For this reason, the Ea for different ranges of temperature

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(Figure 1B) was calculated and is presented in Table 1. The flexion point was chosen at 20˚C.

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Ea values of 140 and 46 kJ/mol were determined for the following temperature intervals, 10 -

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20˚C and 20 - 40˚C, respectively. The calculated values are significantly different, but similar

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behaviour was found by Isaka et al. [2008] and Lotti et al. [2015]. Isaka et al. [2008] noticed

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a flexion point at ca. 28˚C and Ea= 93 - 94 kJ/mol (in the range of 6-28˚C) and Ea= 33 kJ/mol

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(in the range of 28-37˚C). Lotti et al. [2015] found a flexion point at ca. 20˚C and also

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ACCEPTED MANUSCRIPT observed that the activation energy increases at lower temperatures. These conclusions can be

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confirmed by the overview as presented in Table 1. The phenomenon described here may be

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connected with anammox reaction steps, which could involve two rate-determining enzymes

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with various temperature optima [Isaka et al., 2008]. On the other hand, the Arrhenius

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equation is valid only in a certain temperature range and can be useless for low temperatures

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(below 15˚C) [Lotti et al., 2015].

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Table 1.

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3.2.Individual pH influence

Anammox bacteria are sensitive to pH changes [Jin et al., 2012], thus controlling the pH is

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essential in the anammox process. In the study presented here the highest activity was

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observed at pH 7.0 and 7.5 (Figure 2). This result is in the range presented in other literature

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data that are summarised in Table 2. Carvajal-Arroyo et al. [2014] conducted a short-term

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effect test in a pH range of 6.8 to 8.2 which shows high SAA (0.6-0.8 gN·gVSS-1·d-1) in the

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full tested range. Strous et al. [1999] described the optimum pH as being between 6.7 and 8.3,

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but other authors [Egli et al., 2001; Tang et al., 2010; Jin et al., 2012] have reported anammox

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activity in a wider range, i.e. from 6.5 to 9.3. Moreover, Figure 2 shows that pH values below

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the optimal range (7.0 – 7.5) caused the strongest inhibition, i.e. than values above this range.

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Almost complete inhibition was obtained in pH 6.0 (0.010 gN·gVSS-1·d-1), whereas at pH 9.0

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activity was much higher (0.224 gN·gVSS-1·d-1). The biomass used in the assay was

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dominated by anammox bacteria of the genus C. Jettenia. Ali et al. [2015] reported growth of

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C. Jettenia caeni at pH range 6.5 to 8.5, with the optimum at 8.0.

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Figure 2.

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Table 2.

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ACCEPTED MANUSCRIPT The results obtained here are in contrast to long-term experiments which indicate stronger

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inhibition of high pH. During continuous operation, decreased activity causes ammonia

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accumulation, which means an increase in the FA concentration and finally process inhibition.

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Process stability loss as described by Tang et al. [2010] in pH levels between 8.7 and 9.05

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was probably caused by a high FA concentration (57-178 mgNH3·L-1). Similarly, in the

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Carvajal-Arroyo et al. [2014] experiment, pH between 8.1 and 8.6 led to an FA concentration

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increase (7.8-20.8 mgNH3·L-1) and loss of process stability. In turn, Jaroszyński et al. [2011]

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obtained, in pH 6.5±0.01, 2.5-times greater activity than in pH 7.8±0.24, with FA

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concentrations of 0.5±0.1 and 8.3±5.1 mgNH3·L-1, respectively. Nitrite as high as 170–250

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mg N-NO2·L-1 caused no deactivation of the anammox consortium, despite 2 days of

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exposure time. Moreover, Yu and Jin [2012] studied more extreme pH values. After 12 hours

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of operation with inflow pH 4 and 10, performance degradation was observed only in the high

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pH, while the FA concentration was 302.5 mgNH3·L-1. For comparison, in the pH influence

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test, initial FA concentrations after substrate injection were ca. 2.7 mgNH3·L-1 at pH 8.0, 7.4

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mgNH3·L-1 at 8.5 and 16.3 mgNH3·L-1 at 9.0 (Figure 2). The results presented in this study

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confirmed that in order to avoid the direct and indirect negative effects of pH, the anammox

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process should be maintained in a scope of pH from 7.0 to 7.5, what is similar with 7.2 – 7.6

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reported by Carvajal-Arroyo et al. [2014] and Puyol et al. [2014a, 2014b].

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3.3.Interactive temperature and pH influence

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The simultaneous effect of pH and temperature was studied for lower than optimal

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temperatures from 10 to 30°C. Batch experiments were performed according to the CCD

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design (Table 3). The lowest SAA (0.021 ± 0.003 gN·gVSS-1·d-1) was given at a temperature

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of 13˚C and pH 6.8, while the highest SAA (0.490 ± 0.029 gN·gVSS-1·d-1) was given at 30˚C

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and pH 7.5. The mathematical relationship of the influence of independent and interactive

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temperature and pH on SAA was approximated by the polynomial quadratic formula (R2 = 9

ACCEPTED MANUSCRIPT 0.96), as shown in equation 2. The obtained model was tested using ANOVA (Supplementary

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Table 1).

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SAA = -5.92259 - 0.00731 T + 1.46833 pH + 0.00012 T2 - 0.09422 pH2 + 0.00020 T pH (2)

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Table 3.

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The ANOVA test includes the lack-of-fit test, which provides information about the tested

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model’s lack of fit. The lack-of-fit test result is insignificant (p ≥ 0.05), which indicates that

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the current model is suitable to describe the relationship between the studied parameters

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[StatSoft, 2013]. Statistical analysis also confirmed that both temperature and pH affect

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anammox activity (high Fisher (F) value and p ≤ 0.05), but it did not show any statistically

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significant interaction between the two parameters (p = 0.95). Consistent results were

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obtained by Daverey et al. [2015] for a temperature range of 21.9 – 43.1˚C and pH 5.38 –

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9.62. On the other hand, Daverey et al. [2015] also suggested the presence of interaction

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between temperature and pH based on the elliptical shape of the contour plot. Likewise,

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contour (Supplementary Figure 2A) and response surface (Supplementary Figure 2B) plots

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were constructed to obtain a better visualisation of the relationship between SAA and levels

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of temperature and pH.

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The contour plots are elliptical, but the shapes of the plots are not caused by interaction

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between temperature and pH (as confirmed by ANOVA, Supplementary Table 1). Plots

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shapes result only from the independent pH effect, as the shape of the relationship between

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pH and SAA (Supplementary Figure 2A) is similar to that obtained in the individual pH

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influence test (Figure 2). Moreover, the optimal pH was given in a constant value in the full

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tested temperature range and was ca. 7.8. It was slightly higher than previously shown in the

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individual pH influence test (i.e. it was 7 and 7.5), but both tests were conducted with several

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weeks interval. Because the biomass that was used was cultivated in a reactor with varying

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ACCEPTED MANUSCRIPT pH, the individual pH influence test was conducted on biomass working at pH ca. 7.7, when

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in the CCD experiment it was ca. 8.0. The difference in optimal pH can be associated with the

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type of adaptation, which is more proof that adaptation is a very important factor in anammox

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cultivation.

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Daverey et al. [2015] assumed that the negative effect of low temperature can be compensated

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for by higher pH. This conclusion was made based on two experimental sets in 15˚C with pH

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6.5 and 7.5. An analysis of the results here shows that this is a case of optimal pH, as the

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optimal pH range narrows along with a temperature decrease, as is shown in Figure 3. It also

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shows the SAA at 10, 13, 20, 27 and 30°C, depending on the pH level. High activity in 30, 27

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and 20 °C was observed in wide pH ranges. In 13 °C activity was noted only from ca. 6.8 to

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8.8, while in 10 °C it only takes place from ca. 7.3 to 8.3. This indicates that anammox

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performance at a low temperature may be supported by more accurate pH control.

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Figure 3.

4. Conclusions

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Optimal pH was observed between 7.0 and 7.5 and values below this optimal range caused the

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strongest activity inhibition than values above this range. Temperature ca. 15-20 °C

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constitutes some kind of breaking point for the metabolism of anammox bacteria. The CCD

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results indicate that both temperature and pH affect anammox activity, but there is no

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statistically significant interaction between these two parameters. However, the optimal pH

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range narrows along with a temperature decrease, which means that the efficiency of the

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anammox process at low temperatures can be improved by correction and adequate control of

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pH.

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Acknowledgement

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The work was supported by the Polish National Science Centre [UMO-2013/09/D/NZ9/02438]

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ambient temperature. Chem. Eng. J., 232, 17-25, 2013.

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physiology, cell biology, and metabolism. Adv. Microb. Physiol., 60, 211–262, 2012.

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scale partial nitritation/anammox experiences - an application survey. Water Res., 55, 292-

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temperatures. Bioresour. Technol., 129, 606-611, 2013.

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Ma B., Wang S., Cao S., Miao Y., Jia F., Du R., Peng Y.: Biological nitrogen removal from

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sewage via anammox: Recent advantages. Bioresour. Technol., 200, 981-990, 2016.

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granular biomass – short and long-term aspect. Conference Proceedings, IWA Specialist

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Figures captions

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Figure 1 (A) Temperature (with constant pH 7.5) influence on specific anammox activity (SAA) obtained

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in batch test experiments (bars represent standard deviation of the mean from duplicate). (B) Arrhenius

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plots for the anammox conversion with regression lines for different temperature intervals. Solid line: 10 -

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40˚C, thin dotted line: 10 - 20˚C, thick dotted line: 20 - 40˚C.

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Figure 2 pH (with constant temperature 30°C) influence on Specific Anammox Activity (SAA) obtained in

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batch test experiments. Bars: standard deviation of the mean from duplicate; dots: initial free ammonia

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(FA) concentration.

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Figure 3 pH influence on SAA (Specific Anammox Activity) for respectively 10, 13, 20, 27 and 30°C. Lines

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present values calculated by polynomial equation, while points present values obtained in batch tests.

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Tables

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Table 1 Results and overview of activation energy of anammox reaction for different temperature ranges. References

Suspended sludge Suspended sludge Entrapped with gel carrier Granular Granular Suspended sludge Aggregated Granular and biofilm Suspended sludge Suspended sludge Suspended sludge Granular Entrapped with gel carrier

This study Lotti et al. [2015] Isaka et al. [2008] Sobotka et al. [2015] Hendrickx et al. [2012] This study Strous et al. [1999] Dosta et al. [2008] Hendrickx et al. [2014] Lotti et al. [2015] This study Jin et al. [2013] Isaka et al. [2008]

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Anammox biomass

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Apparent activation energy [kJ mol-1] 140 124 93 - 94 76 72 72 70 63 66 48 46 43 33

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Temperature range [˚C] 10 - 20 10 - 20 6 - 28 10 - 40 10 - 20 10 - 40 20 - 43 10 - 40 5 - 17 20 - 30 20 - 40 15 - 35 28 - 37

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Table 2 Overview of the anammox optimal pH range. References This study Lu et al. [2016] Carvajal-Arroyo et al. [2014] Puyol et al. [2014b] van Hulle et al. [2007] Yang et al. [2006] Egli et al. [2001] Strous et al. [1999]

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Optimal pH 7.0-7.5 ~7.6 ~7.4 7.2-7.6 6.5-8.0 7.5-8.3 ~8 6.7-8.3

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Table 3 CCD experimental plan (α≈ 1.41) and results with calculated initial free ammonia (FA) and free

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nitrous acid (FNA) concentrations. T – temperature, SAA – Specific Anammox Activity, SD – standard

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deviation of the mean from duplicate.

T [°C]

pH

20 10 13 20 27 20 20 20 20 27 30 13

7.5 7.5 6.8 7.5 8.2 7.5 8.5 7.5 6.5 6.8 7.5 8.2

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Initial concentration FNA FA [mgNH3·L-1] [mgHNO2·L-1] 1.049 0.019 0.491 0.025 0.053 0.049 0.450 0.008 3.425 0.001 0.450 0.008 4.046 0.001 0.450 0.008 0.045 0.080 0.150 0.033 0.907 0.006 1.295 0.002

SAA [gN·gVSS-1·d-1]

SD

0.256 0.032 0.021 0.302 0.464 0.241 0.235 0.266 0.075 0.436 0.490 0.053

0.005 0.006 0.003 0.035 0.001 0.023 0.029 0.023 0.011 0.047 0.029 0.012

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Coded values (T, pH) 0,0 -α , 0 -1 , -1 0,0 +1 , +1 0,0 0 , +α 0,0 0 , -α +1 , -1 +α , 0 -1 , +1

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0.5 0.4 0.3

0.1 0.0 6.5

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7.5 pH

30 °C

27 °C

20 °C

30 °C

27 °C

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Highlights •

15-20°C constitutes breaking point for the anammox bacteria metabolism.

•

No statistically significant interaction between pH and low temperature.

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• Appropriate pH control can improves anammox efficiency at low temperatures.